Quantum reservoir computing with metastable dynamics

Metastability characterizes the long transient relaxation towards a stable state of certain dissipative dynamical systems, including quantum ones. Interestingly, metastable behaviour has been described in the interaction between neurons in the brain and it has been shown as a mechanism to have associative memories. The aim of this project is to explore the effect of this phenomenon in quantum reservoir computing, a machine learning approach inspired by neuromorphic computation. We will focus on a nonlinear oscillator with dissipation in the formalism of quantum master equations, we will design a suitable reservoir computing architecture, and finally we will address the performance of this machine learning approach for time series processing in the metastable regime.

TFM Supervisors: Roberta Zambrini and Gian Luca Giorgi

TFM Committee: Damià Gomila, Miguel C. Soriano, and Gian Luca Giorgi

This online event can be followed at:

https://us06web.zoom.us/j/86154493052?pwd=zvCz4trayc7aQnEubOAmAbq9CYaAW7.1